KTP Associate in AI & Robotics for Recycling

KTP
Knowledge Transfer Partnerships (KTPs) are a unique UK-wide activity that help businesses to improve their competitiveness and productivity by making better use of the knowledge, technology and skills within universities, colleges and research organisations.

Further information is available at: https://iuk-ktp.org.uk/ 

THE PROJECT
The University of Essex, in partnership with Firstgrade, offers an exciting opportunity to a graduate with the relevant skills and knowledge to revolutionise waste sorting in skips by developing an AI-powered system that automatically screens and sorts mixed construction waste with greater speed, accuracy, and efficiency.

DUTIES OF THE POST
These will include:

• Designing and implementing AI and sensor-based solutions for automated waste recognition and sorting.
• Developing and training deep learning models for waste recognition, classification, and segmentation using multimodal sensor data (RGB, NIR, depth).
• Designing, calibrating, and integrating multi-sensor acquisition systems for real-time industrial waste sorting environments.
• Deploying and optimising AI models on edge-computing devices to achieve low-latency, high-throughput performance.
• Integrating AI perception outputs with mechanical conveyor and actuation systems for automated sorting control.
• Testing, validating, and refining the integrated AI-based waste sorting system under industrial operating conditions, ensuring robustness and scalability.
• Supporting company scale up and exploitation of new technology.
• Acting as project lead, to progress the project and ensure milestones are met to a timely manner.
• Embedding technology, training and upskilling company staff.
• Participating in academic and/or industrial conferences and other events, to disseminate and present research outcomes to the wider community.

These duties are a guide to the work that the post holder will initially be required to undertake and may change from time to time.

KEY REQUIREMENTS

Qualifications:

• BSc in Computer Science, Electronic Engineering, Robotics, or a related field.
• MSc or equivalent industry experience in Artificial Intelligence, Computer Vision, or Embedded Systems.

Skills/Knowledge:

• Strong understanding of machine learning and computer vision, including supervised/unsupervised learning methods.
• Knowledge of image processing, feature extraction, and sensor calibration techniques.
• Experience employing deep learning frameworks (e.g. PyTorch, TensorFlow).
• Experience implementing object detection/classification models (e.g. YOLO, Faster R-CNN).
• Proficiency in Python and C/C++, with experience of software engineering best practices (e.g., version control, testing).
• Experience developing real-time systems, edge computing solutions (e.g. NVIDIA Jetson), and sensor fusion algorithms.
• Understanding of data acquisition and annotation processes, and practical experience with tools such as Label Studio or Roboflow.
• Awareness of health and safety considerations when working with industrial equipment.

Attributes:

• Strong analytical and problem-solving skills.
• Ability to work as part of a team and to work independently and manage own workload effectively.
• Willingness to engage in hands-on testing in industrial environments.
• Excellent communication and interpersonal skills, with the ability to collaborate across academic, industrial, and technical stakeholders and to explain technical concepts to non-technical colleagues.
• Self-motivated, proactive, and able to take initiative in progressing project tasks.
• Commitment to professional development and continuous learning.

LOCATION
Firstgrade Recycling Systems Limited
Unit 2 Crossways
Cockfield
Bury St Edmunds
Suffolk
IP30 0LN

Please use the 'Apply' button to read further information about this role including the full job description and person specification which outlines the full duties, skills, qualifications and experience needed for this role. You will also find details of how to make your application here.

Our website http://www.essex.ac.uk contains more information about the University of Essex. If you have a disability and would like information in a different format, please email resourcing@essex.ac.uk.

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